Projects Last Projects
DeepFlowers - Online Flower Recognition using Deep Neural Networks
Yonatan Zarecki and Ziv Izhar
Supervised by Elad Richardson
These days, it seems like everyone has their own smartphone and that internet connection is available everywhere even in the most distant corners of nature reserves. A challenging task for nature lovers is the task of flower recognition, even with heavy big and heavy flower guide books it is hard to identify each flower species exactly, and for amateurs finding anything is using these guides can be a monumental task by itself, Differences between flowers species can be very subtle, and not easy to detect even for an expert's eye. Another challenge a flower classifier has to face is the sheer amount of flowers in the world, or in a specific country.
In this project we try and harvest the power of deep convolutional neural networks (CNNs) for our recognition task which have proven to be successful in similar tasks, and using data given to us by Prof. Avi Shmida of the Hebrew University, build a flower recognizer with an open online API for all to use.
Please, see project report.
Please, see final presentation.